Diffusion-weighting Caused by Spoiler Gradients in the Fast Imaging with Steady-state Precession Sequence May Lead to Inaccurate T2 Measurements in MR Fingerprinting

Three-dimensional Multi-parameter Mapping of Relaxation Times and Susceptibility Using Partially RF-spoiled Gradient Echo

PURPOSE

MR parameter mapping is a technique that obtains distributions of parameters such as relaxation time and proton density (PD) and is starting to be used for disease quantification in clinical diagnoses. Quantitative susceptibility mapping is also promising for the early diagnosis of brain disorders such as degenerative neurological disorders. Therefore, we developed an MR quantitative parameter mapping (QPM) method to map four tissue-related parameters (T1, T2*, PD, and susceptibility) and B1 simultaneously by using a 3D partially RF-spoiled gradient echo (pRSGE). We verified the accuracy and repeatability of QPM in phantom and volunteer experiments.

METHODS

Tissue-related parameters are estimated by varying four scan parameters of the 3D pRSGE: flip angle, RF-pulse phase increment, TR and TE, performing multiple image scans, and finding a least-squares fit for an intensity function (which expresses the relationship between the scan parameters and intensity values). The intensity function is analytically complex, but by using a Bloch simulation to create it numerically, the least-squares fitting can be used to estimate the quantitative values. This has the advantage of shortening the image-reconstruction processing time needed to estimate the quantitative values than with methods using pattern matching.

RESULTS

A 1.1-mm isotropic resolution scan covering the whole brain was completed with a scan time of approximately 12 minutes, and the reconstruction time using a GPU was approximately 1 minute. The phantom experiments confirmed that both the accuracy and repeatability of the quantitative values were high. The volunteer scans also confirmed that the accuracy of the quantitative values was comparable to that of conventional methods.

CONCLUSION

The proposed QPM method can map T1, T2*, PD, susceptibility, and B1 simultaneously within a scan time that can be applied to human subjects.

Accuracy, repeatability, and reproducibility of T1 and T2 relaxation times measurement by 3D magnetic resonance fingerprinting with different dictionary resolutions

OBJECTIVES

To assess the accuracy, repeatability, and reproducibility of T₁ and T₂ relaxation time measurements by three-dimensional magnetic resonance fingerprinting (3D MRF) using various dictionary resolutions.

METHODS

The ISMRM/NIST phantom was scanned daily for 10 days in two 3 T MR scanners using a 3D MRF sequence reconstructed using four dictionaries with varying step sizes and one dictionary with wider ranges. Thirty-nine healthy volunteers were enrolled: 20 subjects underwent whole-brain MRF scans in both scanners and the rest in one scanner. ROI/VOI analyses were performed on phantom and brain MRF maps. Accuracy, repeatability, and reproducibility metrics were calculated.

RESULTS

In the phantom study, all dictionaries showed high T₁ linearity to the reference values (R² > 0.99), repeatability (CV < 3%), and reproducibility (CV < 3%) with lower linearity (R² > 0.98), repeatability (CV < 6%), and reproducibility (CV ≤ 4%) for T₂ measurement. The volunteer study demonstrated high T₁ reproducibility of within-subject CV (wCV) < 4% by all dictionaries with the same ranges, both in the brain parenchyma and CSF. Yet, reproducibility was moderate for T₂ measurement (wCV < 8%). In CSF measurement, dictionaries with a smaller range showed a seemingly better reproducibility (T₁, wCV 3%; T₂, wCV 8%) than the much wider range dictionary (T₁, wCV 5%; T₂, wCV 13%). Truncated CSF relaxometry values were evident in smaller range dictionaries.

CONCLUSIONS

The accuracy, repeatability, and reproducibility of 3D MRF across various dictionary resolutions were high for T₁ and moderate for T₂ measurements. A lower-resolution dictionary with a well-defined range may be adequate, thus significantly reducing the computational load.

KEY POINTS

• A lower-resolution dictionary with a well-defined range may be sufficient for 3D MRF reconstruction. • CSF relaxation times might be underestimated due to truncation by the upper dictionary range. • Dictionary with a higher upper range might be advisable, especially for CSF evaluation and elderly subjects whose perivascular spaces are more prominent.

Efficient performance analysis and optimization of transient-state sequences for multiparametric magnetic resonance imaging

In transient-state multiparametric MRI sequences such as Magnetic Resonance Spin TomogrAphy in Time-domain (MR-STAT), MR fingerprinting, or hybrid-state imaging, the flip angle pattern of the RF excitation varies over the sequence. This gives considerable freedom to choose an optimal pattern of flip angles. For pragmatic reasons, most optimization methodologies choose for a single-voxel approach (i.e., without taking the spatial encoding scheme into account). Particularly in MR-STAT, the context of spatial encoding is important. In the current study, we present a methodology, called BLock Analysis of a K-space-domain Jacobian (BLAKJac), which is sufficiently fast to optimize a sequence in the context of a predetermined phase-encoding pattern. Based on MR-STAT acquisitions and reconstructions, we show that sequences optimized using BLAKJac are more reliable in terms of actually achieved precision than conventional single-voxel-optimized sequences. In addition, BLAKJac provides analytical tools that give insights into the performance of the sequence in a very limited computation time. Our experiments are based on MR-STAT, but the theory is equally valid for other transient-state multiparametric methods.

MR Fingerprinting for Liver Tissue Characterization: A Histopathologic Correlation Study

Background Liver MR fingerprinting (MRF) enables simultaneous quantification of T1, T2, T2*, and proton density fat fraction (PDFF) maps in single breath-hold acquisitions. Histopathologic correlation studies are desired for its clinical use. Purpose To compare liver MRF-derived metrics with separate reference quantitative MRI in participants with diffuse liver disease, evaluate scan-rescan repeatability of liver MRF, and validate MRF-derived measurements for histologic grading of liver biopsies. Materials and Methods This prospective study included participants with diffuse liver disease undergoing MRI from July 2021 to January 2022. Participants underwent two-dimensional single-section liver MRF and separate reference quantitative MRI. Linear regression, Bland-Altman plots, and coefficients of variation were used to assess the bias and repeatability of liver MRF measurements. For participants undergoing liver biopsy, the association between mapping and histologic grading was evaluated by using the Spearman correlation coefficient. Results Fifty-six participants (mean age, 59 years ± 15 [SD]; 32 women) were included to compare mapping techniques and 23 participants were evaluated with liver biopsy (mean age, 52.7 years ± 12.7; 14 women). The linearity of MRF with reference measurements in participants with diffuse liver disease (R² value) for T1, T2, T2*, and PDFF maps was 0.86, 0.88, 0.54, and 0.99, respectively. The overall coefficients of variation for repeatability in the liver were 3.2%, 5.5%, 7.1%, and 4.6% for T1, T2, T2*, and PDFF maps, respectively. MRF-derived metrics showed high diagnostic performance in differentiating moderate or severe changes from mild or no changes (area under the receiver operating characteristic curve for fibrosis, inflammation, steatosis, and siderosis: 0.62 [95% CI: 0.52, 0.62], 0.92 [95% CI: 0.88, 0.92], 0.97 [95% CI: 0.96, 0.97], and 0.74 [95% CI: 0.57, 0.74], respectively). Conclusion Liver MR fingerprinting provided repeatable T1, T2, T2*, and proton density fat fraction maps in high agreement with reference quantitative mapping and may correlate with pathologic grades in participants with diffuse liver disease. © RSNA, 2022 Online supplemental material is available for this article.

3D MR fingerprinting using Seiffert spirals

PURPOSE

Seiffert spirals were recently explored as an efficient way to traverse 3D k-space compared to traditional 3D techniques. Several studies have shown the ability of 3D MR fingerprinting (MRF) techniques to acquire T₁ and T₂ relaxation maps in a short period of time. However, these sequences do not sample across a large region of 3D k-space every TR, especially in the way that Seiffert trajectories can.

METHODS

A 3D MRF sequence was designed using 8 Seiffert spirals rotated in 3D k-space, with flip angle modulation for T₁ and T₂ sensitivity. The sequence was compared to an MRF sequence using a 2D spiral rotated in 3D k-space using the tiny golden angle acquisition with similar resolution/readout duration. Both sequences were evaluated using simulations, phantom validation, and in vivo imaging.

RESULTS

In all experiments, the Seiffert spiral MRF sequence performed similar to if not better than the multi-axis 2D spiral MRF sequence. Strong intraclass correlation coefficients (> 0.9) were found between conventional and MRF sequences in phantoms, whereas the in vivo results showed slightly less aliasing artifact with the Seiffert trajectory.

CONCLUSION

In this study, Seiffert spirals were used within the MRF framework to acquire high-resolution T₁ and T₂ relaxation time maps in less than 2.5 min. The reduced aliasing artifacts seen with the Seiffert sequence suggests that sampling over 3D k-space evenly each TR can improve quantification or shorten scan times.

Characterization of cardiac amyloidosis using cardiac magnetic resonance fingerprinting

BACKGROUND

Cardiac amyloidosis (CA) is an infiltrative cardiomyopathy with poor prognosis absent appropriate treatment. Elevated native myocardial T₁ and T₂ have been reported for CA, and tissue characterization by cardiac MRI may expedite diagnosis and treatment. Cardiac Magnetic Resonance Fingerprinting (cMRF) has the potential to enable tissue characterization for CA through rapid, simultaneous T₁ and T₂ mapping. Furthermore, cMRF signal timecourses may provide additional information beyond myocardial T₁ and T₂.

METHODS

Nine CA patients and five controls were scanned at 3 T using a prospectively gated cMRF acquisition. Two cMRF-based analysis approaches were examined: (1) relaxometric-based linear discriminant analysis (LDA) using native T₁ and T₂, and (2) signal timecourse-based LDA. The Fisher coefficient was used to compare the separability of patient and control groups from both approaches. Leave-two-out cross-validation was employed to evaluate the classification error rates of both approaches.

RESULTS

Elevated myocardial T₁ and T₂ was observed in patients vs controls (T₁: 1395 ± 121 vs 1240 ± 36.4 ms, p < 0.05; T₂: 36.8 ± 3.3 vs 31.8 ± 2.6 ms, p < 0.05). LDA scores were elevated in patients for relaxometric-based LDA (0.56 ± 0.28 vs 0.18 ± 0.13, p < 0.05) and timecourse-based LDA (0.97 ± 0.02 vs 0.02 ± 0.02, p < 0.05). The Fisher coefficient was greater for timecourse-based LDA (60.8) vs relaxometric-based LDA (1.6). Classification error rates were lower for timecourse-based LDA vs relaxometric-based LDA (12.6 ± 24.3 vs 22.5 ± 30.1%, p < 0.05).

CONCLUSIONS

These findings suggest that cMRF may be a valuable technique for the detection and characterization of CA. Analysis of cMRF signal timecourse data may improve tissue characterization as compared to analysis of native T₁ and T₂ alone.

Myocardial T1, T2, T2*, and fat fraction quantification via low-rank motion-corrected cardiac MR fingerprinting

Purpose

Develop a novel 2D cardiac MR fingerprinting (MRF) approach to enable simultaneous T1, T2, T2*, and fat fraction (FF) myocardial tissue characterization in a single breath‐hold scan.

Methods

Simultaneous, co‐registered, multi‐parametric mapping of T1, T2, and FF has been recently achieved with cardiac MRF. Here, we further incorporate T2* quantification within this approach, enabling simultaneous T1, T2, T2*, and FF myocardial tissue characterization in a single breath‐hold scan. T2* quantification is achieved with an eight‐echo readout that requires a long cardiac acquisition window. A novel low‐rank motion‐corrected (LRMC) reconstruction is exploited to correct for cardiac motion within the long acquisition window. The proposed T1/T2/T2*/FF cardiac MRF was evaluated in phantom and in 10 healthy subjects in comparison to conventional mapping techniques.

Results

The proposed approach achieved high quality parametric mapping of T1, T2, T2*, and FF with corresponding normalized RMS error (RMSE) T1 = 5.9%, T2 = 9.6% (T2 values <100 ms), T2* = 3.3% (T2* values <100 ms), and FF = 0.8% observed in phantom scans. In vivo, the proposed approach produced higher left‐ventricular myocardial T1 values than MOLLI (1148 vs 1056 ms), lower T2 values than T2‐GraSE (42.8 vs 50.6 ms), lower T2* values than eight‐echo gradient echo (GRE) (35.0 vs 39.4 ms), and higher FF values than six‐echo GRE (0.8 vs 0.3 %) reference techniques. The proposed approach achieved considerable reduction in motion artifacts compared to cardiac MRF without motion correction, improved spatial uniformity, and statistically higher apparent precision relative to conventional mapping for all parameters.

Conclusion

The proposed cardiac MRF approach enables simultaneous, co‐registered mapping of T1, T2, T2*, and FF in a single breath‐hold for comprehensive myocardial tissue characterization, achieving higher apparent precision than conventional methods.

Feasibility of Magnetic Resonance Fingerprinting on Aging MRI Hardware

The purpose of this work is to evaluate the feasibility of performing magnetic resonance fingerprinting (MRF) on older and lower-performance MRI hardware as a means to bring advanced imaging to the aging MRI install base. Phantom and in vivo experiments were performed on a 1.5T Siemens Aera (installed 2015) and 1.5T Siemens Symphony (installed 2002). A 2D spiral MRF sequence for simultaneous T₁/T₂/M₀ mapping was implemented on both scanners with different gradient trajectories to accommodate system specifications. In phantom, for T₁/T₂ values in a physiologically relevant range (T₁: 195-1539 ms; T₂: 20-267 ms), scanners had strong correlation (R² > 0.999) with average absolute percent difference of 8.1% and 10.1%, respectively. Comparison of the two trajectories on the newer scanner showed differences of 2.6% (T₁) and 10.9% (T₂), suggesting a partial explanation of the observed inter-scanner bias. Inter-scanner agreement was better when the same trajectory was used, with differences of 6.0% (T₁) and 4.0% (T₂). Intra-scanner coefficient of variation (CV) of T₁ and T₂ estimates in phantom were <2.0% and in vivo were ≤3.5%. In vivo inter-scanner white matter CV was 4.8% (T₁) and 5.1% (T₂). White matter measurements on the aging scanner after two months were consistent, with differences of 1.9% (T₁) and 3.9% (T₂). In conclusion, MRF is feasible on an aging MRI scanner and required only changes to the gradient trajectory.

Simultaneous T1 , T2 , and T1ρ cardiac magnetic resonance fingerprinting for contrast agent-free myocardial tissue characterization

PURPOSE

To develop a simultaneous T₁ , T₂ , and T_1ρ cardiac magnetic resonance fingerprinting (MRF) approach to enable comprehensive contrast agent-free myocardial tissue characterization in a single breath-hold scan.

METHODS

A 2D gradient-echo electrocardiogram-triggered cardiac MRF sequence with low flip angles, varying magnetization preparation, and spiral trajectory was acquired at 1.5 T to encode T₁ , T₂ , and T_1⍴ simultaneously. The MRF images were reconstructed using low-rank inversion, regularized with a multicontrast patch-based higher-order reconstruction. Parametric maps were generated and matched in the singular value domain to extended phase graph-based dictionaries. The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional methods in terms of coefficients of determination and best fits for the phantom study, and in terms of Bland-Altman agreement, average values and coefficient of variation of T₁ , T₂ , and T_1⍴ for the healthy subjects study.

RESULTS

The T₁ , T₂ , and T_1⍴ MRF values showed excellent correlation with conventional spin-echo and clinical mapping methods in phantom studies (r² > 0.97). Measured MRF values in myocardial tissue (mean ± SD) were 1133 ± 33 ms, 38.8 ± 3.5 ms, and 52.0 ± 4.0 ms for T₁ , T₂ and T1_⍴ , respectively, against 1053 ± 47 ms, 50.4 ± 3.9 ms, and 55.9 ± 3.3 ms for T₁ modified Look-Locker inversion imaging, T₂ gradient and spin echo, and T_1⍴ turbo field echo, respectively.

CONCLUSION

A cardiac MRF approach for simultaneous quantification of myocardial T₁ , T₂ , and T_1ρ in a single breath-hold MR scan of about 16 seconds has been proposed. The approach has been investigated in phantoms and healthy subjects showing good agreement with reference spin echo measurements and conventional clinical maps.

Simultaneous comprehensive liver T1 , T2 , T 2 ∗ , T1ρ , and fat fraction characterization with MR fingerprinting

PURPOSE

To develop a novel simultaneous co-registered T₁ , T₂ , T 2 ∗ , T_1ρ , and fat fraction abdominal MR fingerprinting (MRF) approach for fully comprehensive liver-tissue characterization in a single breath-hold scan.

METHODS

A gradient-echo liver MRF sequence with low fixed flip angle, multi-echo radial readout, and varying magnetization preparation pulses for multiparametric encoding is performed at 1.5 T. The T 2 ∗ and fat fraction are estimated from a graph/cut water/fat separation method using a six-peak fat model. Water/fat singular images obtained are then matched to an MRF dictionary, estimating water-specific T₁ , T₂ , and T_1ρ . The proposed approach was tested in phantoms and 10 healthy subjects and compared against conventional sequences.

RESULTS

For the phantom studies, linear fits show excellent coefficients of determination (r² > 0.9) for every parametric map. For in vivo studies, the average values measured within regions of interest drawn on liver, spleen, muscle, and fat are statistically different from the reference scans (p < 0.05) for T₁ , T₂ , and T_1⍴ but not for T 2 ∗ and fat fraction, whereas correlation between MRF and reference scans is excellent for each parameter (r² > 0.92 for every parameter).

CONCLUSION

The proposed multi-echo inversion-recovery, T₂ , and T_1⍴ prepared liver MRF sequence presented in this work allows for quantitative T₁ , T₂ , T 2 ∗ , T_1⍴ , and fat fraction liver-tissue characterization in a single breath-hold scan of 18 seconds. The approach showed good agreement and correlation with respect to reference clinical maps.

A unifying view on extended phase graphs and Bloch simulations for quantitative MRI

Quantitative MRI methods and learning-based algorithms require exact forward simulations. One critical factor to correctly describe magnetization dynamics is the effect of slice-selective RF pulses. While contemporary simulation techniques correctly capture their influence, they only provide final magnetization distributions, require to be run for each parameter set separately, and make it hard to derive general theoretical conclusions and to generate a fundamental understanding of echo formation in the presence of slice-profile effects. This work aims to provide a mathematically exact framework, which is equally intuitive as extended phase graphs (EPGs), but also considers slice-profiles through their natural spatial representation. We show, through an analytical, hybrid Bloch-EPG formalism, that the spatially-resolved EPG approach allows to exactly predict the signal dependency on off-resonance, spoiling moment, microscopic dephasing, and echo time. We also demonstrate that our formalism allows to use the same phase graph to simulate both gradient-spoiled and balanced SSFP-based MR sequences. We present a derivation of the formalism and identify the connection to existing methods, i.e. slice-selective Bloch, slice-selective EPG, and the partitioned EPG. As a use case, the proposed hybrid Bloch-EPG framework is applied to MR Fingerprinting.

Generalized low-rank nonrigid motion-corrected reconstruction for MR fingerprinting

PURPOSE

Develop a novel low-rank motion-corrected (LRMC) reconstruction for nonrigid motion-corrected MR fingerprinting (MRF).

METHODS

Generalized motion-corrected (MC) reconstructions have been developed for steady-state imaging. Here we extend this framework to enable nonrigid MC for transient imaging applications with varying contrast, such as MRF. This is achieved by integrating low-rank dictionary-based compression into the generalized MC model to reconstruct MC singular images, reducing motion artifacts in the resulting parametric maps. The proposed LRMC reconstruction was applied for cardiac motion correction in 2D myocardial MRF (T₁ and T₂ ) with extended cardiac acquisition window (~450 ms) and for respiratory MC in free-breathing 3D myocardial and 3D liver MRF. Experiments were performed in phantom and 22 healthy subjects. The proposed approach was compared with reference spin echo (phantom) and with 2D electrocardiogram-triggered/breath-hold MOLLI and T₂ gradient-and-spin echo conventional maps (in vivo 2D and 3D myocardial MRF).

RESULTS

Phantom results were in general agreement with reference spin-echo measurements, presenting relative errors of approximately 5.4% and 5.5% for T₁ and short T₂ (<100 ms), respectively. The proposed LRMC MRF reduced residual blurring artifacts with respect to no MC for cardiac or respiratory motion in all cases (2D and 3D myocardial, 3D abdominal). In 2D myocardial MRF, left-ventricle T₁ values were 1150 ± 41 ms for LRMC MRF and 1010 ± 56 ms for MOLLI; T₂ values were 43.8 ± 2.3 ms for LRMC MRF and 49.5 ± 4.5 ms for T₂ gradient and spin echo. Corresponding measurements for 3D myocardial MRF were 1085 ± 30 ms and 1062 ± 29 ms for T₁ , and 43.5 ± 1.9 ms and 51.7 ± 1.7 ms for T₂ . For 3D liver, LRMC MRF measured liver T₁ at 565 ± 44 ms and liver T₂ at 35.4 ± 2.4 ms.

CONCLUSION

The proposed LRMC reconstruction enabled generalized (nonrigid) MC for 2D and 3D MRF, both for cardiac and respiratory motion. The proposed approach reduced motion artifacts in the MRF maps with respect to no motion compensation and achieved good agreement with reference measurements.

Quantitative MR relaxation using MR fingerprinting with fractional-order signal evolution

The fractional-order Bloch equations have been shown to describe a wider range of experimental situations involving heterogeneous, porous, or composite materials. This paper introduces a novel dictionary of quantitative MR fingerprinting generated by signal evolution model with fractional-order Bloch equations to describe magnetic resonance (MR) relaxation. Here, the fractional-order relaxation models are implemented into Bloch equations through phase transitions using EPG simulation. In the phantom experiments, the fractional-order analysis showed smaller root mean squared error (T1: RMSE = 5.21%, T2: RMSE=3.75%) using the proposed method compared to using conventional method. Among the in vivo experiments of human brains, the estimated T1 and T2 values (mean ± SD) were 843 ± 46.3 ms and 70 ± 4.7 ms in white matter, 1323 ± 28.5 ms and 95 ± 3.8 ms in gray matter. So the proposed method can provide well extensions of current MR fingerprinting and has shown potential to apply into the phantom experiments and the in vivo applications to approach the standard methods for quantitative imaging.

Efficiency analysis for quantitative MRI of T1 and T2 relaxometry methods

This study presents a comparison of quantitative MRI methods based on an efficiency metric that quantifies their intrinsic ability to extract information about tissue parameters. Under a regime of unbiased parameter estimates, an intrinsic efficiency metricηwas derived for fully-sampled experiments which can be used to both optimize and compare sequences. Here we optimize and compare several steady-state and transient gradient-echo based qMRI methods, such as magnetic resonance fingerprinting (MRF), for jointT1andT2mapping. The impact of undersampling was also evaluated, assuming incoherent aliasing that is treated as noise by parameter estimation.In vivovalidation of the efficiency metric was also performed. Transient methods such as MRF can be up to 3.5 times more efficient than steady-state methods, when spatial undersampling is ignored. If incoherent aliasing is treated as noise during least-squares parameter estimation, the efficiency is reduced in proportion to the SNR of the data, with reduction factors of 5 often seen for practical SNR levels.In vivovalidation showed a very good agreement between the theoretical and experimentally predicted efficiency. This work presents and validates an efficiency metric to optimize and compare the performance of qMRI methods. Transient methods were found to be intrinsically more efficient than steady-state methods, however the effect of spatial undersampling can significantly erode this advantage.

A multi-inversion-recovery magnetic resonance fingerprinting for multi-compartment water mapping

PURPOSE

This study aimed at introducing short-T1/T2 compartment to MR fingerprinting (MRF) at 3 T. Water that is bound to myelin macromolecules have significantly shorter T1 and T2 than free water and can be distinguished from free water by multi-compartment analysis.

METHODS

We developed a new multi-inversion-recovery (mIR) water mapping-MRF based on an unbalanced steady-state coherent sequence (FISP). mIR pulses with an interval of 400 or 500 repetition times (TRs) were inserted into the conventional FISP MRF sequence. Data from our proposed mIR MRF was used to quantify different compartments, including myelin water, gray matter free water, and white matter free water, of brain water by virtue of the iterative non-negative least square (NNLS) with reweighting. Three healthy volunteers were scanned with mIR MRF on a clinical 3 T MRI.

RESULTS

Using an extended phase graph simulation, we found that our proposed mIR scheme with four IR pulses allowed differentiation between short and long T1/T2 components. For in vivo experiments, we achieved the quantification of myelin water, gray matter water, and white matter water at an image resolution of 1.17 × 1.17 × 5 mm³/pixel. As compared to the conventional MRF technique with single IR, our proposed mIR improved the detection of myelin water content. In addition, mIR MRF using spiral-in/out trajectory provided a higher signal level compared with that with spiral-out trajectory. Myelin water quantification using mIR MRF with 4 IR and 5 IR pulses were qualitatively similar. Meanwhile, 5 IR MRF showed fewer artifacts in myelin water detection.

CONCLUSION

We developed a new mIR MRF sequence for the rapid quantification of brain water compartments.

Whole-brain 3D MR fingerprinting brain imaging: clinical validation and feasibility to patients with meningioma

Purpose

MR fingerprinting (MRF) is a MR technique that allows assessment of tissue relaxation times. The purpose of this study is to evaluate the clinical application of this technique in patients with meningioma.

Materials and methods

A whole-brain 3D isotropic 1mm³ acquisition under a 3.0T field strength was used to obtain MRF T₁ and T₂-based relaxometry values in 4:38 s. The accuracy of values was quantified by scanning a quantitative MR relaxometry phantom. In vivo evaluation was performed by applying the sequence to 20 subjects with 25 meningiomas. Regions of interest included the meningioma, caudate head, centrum semiovale, contralateral white matter and thalamus. For both phantom and subjects, mean values of both T₁ and T₂ estimates were obtained. Statistical significance of differences in mean values between the meningioma and other brain structures was tested using a Friedman’s ANOVA test.

Results

MR fingerprinting phantom data demonstrated a linear relationship between measured and reference relaxometry estimates for both T₁ (r² = 0.99) and T₂ (r² = 0.97). MRF T₁ relaxation times were longer in meningioma (mean ± SD 1429 ± 202 ms) compared to thalamus (mean ± SD 1054 ± 58 ms; p = 0.004), centrum semiovale (mean ± SD 825 ± 42 ms; p < 0.001) and contralateral white matter (mean ± SD 799 ± 40 ms; p < 0.001). MRF T₂ relaxation times were longer for meningioma (mean ± SD 69 ± 27 ms) as compared to thalamus (mean ± SD 27 ± 3 ms; p < 0.001), caudate head (mean ± SD 39 ± 5 ms; p < 0.001) and contralateral white matter (mean ± SD 35 ± 4 ms; p < 0.001)

Conclusions

Phantom measurements indicate that the proposed 3D-MRF sequence relaxometry estimations are valid and reproducible. For in vivo, entire brain coverage was obtained in clinically feasible time and allows quantitative assessment of meningioma in clinical practice.

Cardiac magnetic resonance fingerprinting: Trends in technical development and potential clinical applications

Quantitative cardiac magnetic resonance has emerged in recent years as an approach for evaluating a range of cardiovascular conditions, with T1 and T2 mapping at the forefront of these developments. Cardiac Magnetic Resonance Fingerprinting (cMRF) provides a rapid and robust framework for simultaneous quantification of myocardial T1 and T2 in addition to other tissue properties. Since the advent of cMRF, a number of technical developments and clinical validation studies have been reported. This review provides an overview of cMRF, recent technical developments, healthy subject and patient studies, anticipated technical improvements, and potential clinical applications. Recent technical developments include slice profile and pulse efficiency corrections, improvements in image reconstruction, simultaneous multislice imaging, 3D whole-ventricle imaging, motion-resolved imaging, fat-water separation, and machine learning for rapid dictionary generation. Future technical developments in cMRF, such as B0 and B1 field mapping, acceleration of acquisition and reconstruction, imaging of patients with implanted devices, and quantification of additional tissue properties are also described. Potential clinical applications include characterization of infiltrative, inflammatory, and ischemic cardiomyopathies, tissue characterization in the left atrium and right ventricle, post-cardiac transplantation assessment, reduction of contrast material, pre-procedural planning for electrophysiology interventions, and imaging of patients with implanted devices.

3D magnetic resonance fingerprinting with quadratic RF phase

PURPOSE

To implement 3D magnetic resonance fingerprinting (MRF) with quadratic RF phase (qRF-MRF) for simultaneous quantification of T₁ , T₂ , ΔB₀ , and T 2 ∗ .

METHODS

3D MRF data with effective undersampling factor of 3 in the slice direction were acquired with quadratic RF phase patterns for T₁ , T₂ , and T 2 ∗ sensitivity. Quadratic RF phase encodes the off-resonance by modulating the on-resonance frequency linearly in time. Transition to 3D brings practical limitations for reconstruction and dictionary matching because of increased data and dictionary sizes. Randomized singular value decomposition (rSVD)-based compression in time and reduction in dictionary size with a quadratic interpolation method are combined to be able to process prohibitively large data sets in feasible reconstruction and matching times.

RESULTS

Accuracy of 3D qRF-MRF maps in various resolutions and orientations are compared to 3D fast imaging with steady-state precession (FISP) for T₁ and T₂ contrast and to 2D qRF-MRF for T 2 ∗ contrast and ΔB₀ . The precision of 3D qRF-MRF was 1.5-2 times higher than routine clinical scans. 3D qRF-MRF ΔB₀ maps were further processed to highlight the susceptibility contrast.

CONCLUSION

Natively co-registered 3D whole brain T₁ , T₂ , T 2 ∗ , ΔB₀ , and QSM maps can be acquired in as short as 5 min with 3D qRF-MRF.

Confounding factors in breast magnetic resonance fingerprinting: B 1 + , slice profile, and diffusion effects

PURPOSE

Magnetic resonance fingerprinting (MRF) offers rapid quantitative imaging but may be subject to confounding effects (CE) if these are not included in the model-based reconstruction. This study characterizes the influence of in-plane B 1 + , slice profile and diffusion effects on T₁ and T₂ estimation in the female breast at 1.5T.

METHODS

Simulations were used to predict the influence of each CE on the accuracy of MRF and to investigate the influence of electronic noise and spiral aliasing artefacts. The experimentally observed bias in regions of fibroglandular tissue (FGT) and fatty tissue (FT) was analyzed for undersampled spiral breast MRF data of 6 healthy volunteers by performing MRF reconstruction with and without a CE.

RESULTS

Theoretic analysis predicts T₁ under-/T₂ overestimation if the nominal flip angles are underestimated and inversely, T₁ under-/T₂ overestimation if omitting slice profile correction, and T₁ under-/T₂ underestimation if omitting diffusion in the signal model. Averaged over repeated signal simulations, including spiral aliasing artefacts affected precision more than accuracy. Strong in-plane B 1 + effects occurred in vivo, causing T₂ left-right inhomogeneity between both breasts. Their correction decreased the T₂ difference from 29 to 5 ms in FGT and from 29 to 9 ms in FT. Slice profile correction affected FGT T₂ most strongly, resulting in -22% smaller values. For the employed spoiler gradient strengths, diffusion did not affect the parameter maps, corresponding well with theoretic predictions.

CONCLUSION

Understanding CEs and their relative significance for an MRF sequence is important when defining an MRF signal model for accurate parameter mapping.

Variability and Standardization of Quantitative Imaging: Monoparametric to Multiparametric Quantification, Radiomics, and Artificial Intelligence

Radiological images have been assessed qualitatively in most clinical settings by the expert eyes of radiologists and other clinicians. On the other hand, quantification of radiological images has the potential to detect early disease that may be difficult to detect with human eyes, complement or replace biopsy, and provide clear differentiation of disease stage. Further, objective assessment by quantification is a prerequisite of personalized/precision medicine. This review article aims to summarize and discuss how the variability of quantitative values derived from radiological images are induced by a number of factors and how these variabilities are mitigated and standardization of the quantitative values are achieved. We discuss the variabilities of specific biomarkers derived from magnetic resonance imaging and computed tomography, and focus on diffusion-weighted imaging, relaxometry, lung density evaluation, and computer-aided computed tomography volumetry. We also review the sources of variability and current efforts of standardization of the rapidly evolving techniques, which include radiomics and artificial intelligence.

An Accurate Dictionary Creation Method for MR Fingerprinting Using a Fast Bloch Simulator

This study proposes an accurate method for creating a dictionary for magnetic resonance fingerprinting (MRF) using a fast Bloch image simulator. An MRF sequence based on a fast imaging with steady precession sequence and a numerical phantom were used for dictionary generation. Cartesian and spiral readout gradients were used for the Bloch image simulation. The validity and usefulness of the method for accurate dictionary creation were demonstrated by MRF parameter maps obtained by pattern matching with the dictionaries generated by the proposed method.

Cardiac cine magnetic resonance fingerprinting for combined ejection fraction, T1 and T2 quantification

This study introduces a technique called cine magnetic resonance fingerprinting (cine-MRF) for simultaneous T₁ , T₂ and ejection fraction (EF) quantification. Data acquired with a free-running MRF sequence are retrospectively sorted into different cardiac phases using an external electrocardiogram (ECG) signal. A low-rank reconstruction with a finite difference sparsity constraint along the cardiac motion dimension yields images resolved by cardiac phase. To improve SNR and precision in the parameter maps, these images are nonrigidly registered to the same phase and matched to a dictionary to generate T₁ and T₂ maps. Cine images for computing left ventricular volumes and EF are also derived from the same data. Cine-MRF was tested in simulations using a numerical relaxation phantom. Phantom and in vivo scans of 19 subjects were performed at 3 T during a 10.9 seconds breath-hold with an in-plane resolution of 1.6 x 1.6 mm² and 24 cardiac phases. Left ventricular EF values obtained with cine-MRF agreed with the conventional cine images (mean bias -1.0%). Average myocardial T₁ times in diastole/systole were 1398/1391 ms with cine-MRF, 1394/1378 ms with ECG-triggered cardiac MRF (cMRF) and 1234/1212 ms with MOLLI; and T₂ values were 30.7/30.3 ms with cine-MRF, 32.6/32.9 ms with ECG-triggered cMRF and 37.6/41.0 ms with T₂ -prepared FLASH. Cine-MRF and ECG-triggered cMRF relaxation times were in good agreement. Cine-MRF T₁ values were significantly longer than MOLLI, and cine-MRF T₂ values were significantly shorter than T₂ -prepared FLASH. In summary, cine-MRF can potentially streamline cardiac MRI exams by combining left ventricle functional assessment and T₁ -T₂ mapping into one time-efficient acquisition.

Slice-selective extended phase graphs in gradient-crushed, transient-state free precession sequences: An application to MR fingerprinting

PURPOSE

Slice-selective, gradient-crushed, transient-state sequences such as those used in MR fingerprinting (MRF) relaxometry are sensitive to slice profile effects. Whereas balanced steady-state free precession MRF profile effects have been studied, less attention has been given to gradient-crushed MRF forms. Extensions of the extended phase graph (EPG) formalism, called slice-selective EPG (ssEPG), are proposed that model slice profile effects.

THEORY AND METHODS

The hard-pulse approximation to slice-selective excitation in the spatial domain is reformulated in k-space. Excitation is modeled by standard EPG shift and transition operators. This ssEPG modeling is validated against Bloch simulations and phantom slice profile measurements. ssEPG relaxometry accuracy and variability are compared with other EPG methods in phantoms and human leg in vivo. The role of ∆B₀ interactions with slice profile and gradient crushers is investigated.

RESULTS

Simulations and slice profile measurements show that ssEPG can model highly dynamic slice profile effects of gradient-crushed sequences. The MRF ssEPG T₂ estimates over 0 < T₂ < 100 ms improve accuracy by > 10 ms at some values relative to other modeling approaches. Small deviations in B₀ can produce substantial bias in T₂ estimations from a range of MRF sequence types, and these effects can be modeled and understood by ssEPG.

CONCLUSION

Transient-state, gradient-crushed sequences such as those used in MRF are sensitive to slice profile effects, and these effects depend on RF pulse choice, gradient crusher strength, and ∆B₀ . It was found ssEPG was the most accurate EPG-based means to model these effects.

T1ρ magnetic resonance fingerprinting

T_1ρ relaxation imaging is a quantitative imaging technique that has been used to assess cartilage integrity, liver fibrosis, tumors, cardiac infarction, and Alzheimer's disease. T₁ , T₂ , and T_1ρ relaxation time constants have each demonstrated different degrees of sensitivity to several markers of fibrosis and inflammation, allowing for a potential multi-parametric approach to tissue quantification. Traditional magnetic resonance fingerprinting (MRF) has been shown to provide quick, quantitative mapping of T₁ and T₂ relaxation time constants. In this study, T_1ρ relaxation is added to the MRF framework using spin lock preparations. An MRF sequence involving an RF-spoiled sequence with T_R , flip angle, T_1ρ , and T₂ preparation variation is described. The sequence is then calibrated against conventional T₁ , T₂ , and T_1ρ relaxation mapping techniques in agar phantoms and the abdomens of four healthy volunteers. Strong intraclass correlation coefficients (ICC > 0.9) were found between conventional and MRF sequences in phantoms and also in healthy volunteers (ICC > 0.8). The highest ICC correlation values were seen in T₁ , followed by T_1ρ and then T₂ . In this study, T_1ρ relaxation has been incorporated into the MRF framework by using spin lock preparations, while still fitting for T₁ and T₂ relaxation time constants. The acquisition of these parameters within a single breath hold in the abdomen alleviates the issues of movement between breath holds in conventional techniques.

A Perspective on MR Fingerprinting

This article reviews the basic concept of MR fingerprinting (MRF) with the goal of highlighting MRF's key contributions, putting them in the context of other quantitative MRI literature, and refining MRF's terminology. The article discusses the robustness and flexibility of MRF's signature dictionary-matching reconstruction along with more advanced MRF reconstructions. A key feature of MRF is the lack of assumptions about the signal evolution, which gives scientists the flexibility to tailor sequences for their needs. The article argues that the concept of unique fingerprints does not capture the requirements for successful parameter mapping and that an analysis of the signal's derivatives with respect to biophysical parameters, such as relaxation times, is more informative, as it allows one to evaluate the efficiency of a pulse sequence. The article points at the source of MRF's efficiency, namely, flip angle variations at the time scale of the relaxation times, and reveals that MRF's advantages are strongest at long scan times, as required for 3D imaging. Further, it outlines how MRF's flexibility can be used to design mutually tailored pulse sequences and biophysical models with the goal of improving the reproducibility of parameter mapping biological tissue. LEVEL OF EVIDENCE: 5 TECHNICAL EFFICACY STAGE: 1.

Acceleration of 2D-MR fingerprinting by reducing the number of echoes with increased in-plane resolution: a volunteer study

Objective

To compare the absolute values and repeatability of magnetic resonance fingerprinting (MRF) with 3000 and 1500 echoes/slice acquired in 41 s and 20 s (MRF3k and MRF1.5k, respectively).

Materials and methods

MRF3k and MRF1.5k scans based on fast imaging with steady precession (FISP) were conducted using a 3 T scanner. Inter-scan agreement and intra-scan repeatability were investigated in 41 and 28 subjects, respectively. Region-of-interest (ROI) analysis was conducted on T1 values of MRF3k by two raters, and their agreement was evaluated using intraclass correlation coefficients (ICCs). Between MRF3k and MRF1.5k, differences in T1 and T2 values and inter-measurement correlation coefficients (CCs) were investigated. Intra-measurement repeatability was evaluated using coefficients of variation (CVs). A p value < 0.05 was considered statistically significant.

Results

The ICCs of ROI measurements were 0.77–0.96. Differences were observed between the two MRF scans, but the CCs of the overall ROIs were 0.99 and 0.97 for the T1 and T2 values, respectively. The mean and median CVs of repeatability were equal to or less than 1.58% and 3.13% in each of the ROIs for T1 and T2, respectively; there were some significant differences between MRF3k and MRF1.5k, but they were small, measuring less than 1%.

Discussion

Both MRF3k and MRF1.5k had high repeatability, and a strong to very strong correlation was observed, with a trend toward slightly higher values in MRF1.5k.

Electronic supplementary material

The online version of this article (10.1007/s10334-020-00842-8) contains supplementary material, which is available to authorized users.

Simultaneous Mapping of T1 and T2 Using Cardiac Magnetic Resonance Fingerprinting in a Cohort of Healthy Subjects at 1.5T

BACKGROUND

Cardiac MR fingerprinting (cMRF) is a novel technique for simultaneous T₁ and T₂ mapping.

PURPOSE

To compare T₁ /T₂ measurements, repeatability, and map quality between cMRF and standard mapping techniques in healthy subjects.

STUDY TYPE

Prospective.

POPULATION

In all, 58 subjects (ages 18-60). FIELD STRENGTH/SEQUENCE: cMRF, modified Look-Locker inversion recovery (MOLLI), and T₂ -prepared balanced steady-state free precession (bSSFP) at 1.5T.

ASSESSMENT

T₁ /T₂ values were measured in 16 myocardial segments at apical, medial, and basal slice positions. Test-retest and intrareader repeatability were assessed for the medial slice. cMRF and conventional mapping sequences were compared using ordinal and two alternative forced choice (2AFC) ratings.

STATISTICAL TESTS

Paired t-tests, Bland-Altman analyses, intraclass correlation coefficient (ICC), linear regression, one-way analysis of variance (ANOVA), and binomial tests.

RESULTS

Average T₁ measurements were: basal 1007.4±96.5 msec (cMRF), 990.0±45.3 msec (MOLLI); medial 995.0±101.7 msec (cMRF), 995.6±59.7 msec (MOLLI); apical 1006.6±111.2 msec (cMRF); and 981.6±87.6 msec (MOLLI). Average T₂ measurements were: basal 40.9±7.0 msec (cMRF), 46.1±3.5 msec (bSSFP); medial 41.0±6.4 msec (cMRF), 47.4±4.1 msec (bSSFP); apical 43.5±6.7 msec (cMRF), 48.0±4.0 msec (bSSFP). A statistically significant bias (cMRF T₁ larger than MOLLI T₁ ) was observed in basal (17.4 msec) and apical (25.0 msec) slices. For T₂ , a statistically significant bias (cMRF lower than bSSFP) was observed for basal (-5.2 msec), medial (-6.3 msec), and apical (-4.5 msec) slices. Precision was lower for cMRF-the average of the standard deviation measured within each slice was 102 msec for cMRF vs. 61 msec for MOLLI T₁ , and 6.4 msec for cMRF vs. 4.0 msec for bSSFP T₂ . cMRF and conventional techniques had similar test-retest repeatability as quantified by ICC (0.87 cMRF vs. 0.84 MOLLI for T₁ ; 0.85 cMRF vs. 0.85 bSSFP for T₂ ). In the ordinal image quality comparison, cMRF maps scored higher than conventional sequences for both T₁ (all five features) and T₂ (four features).

DATA CONCLUSION

This work reports on myocardial T₁ /T₂ measurements in healthy subjects using cMRF and standard mapping sequences. cMRF had slightly lower precision, similar test-retest and intrareader repeatability, and higher scores for map quality.

EVIDENCE LEVEL

2 TECHNICAL EFFICACY: Stage 1 J. Magn. Reson. Imaging 2020;52:1044-1052.

Free-running cardiac magnetic resonance fingerprinting: Joint T1/T2 map and Cine imaging

PURPOSE

To develop and evaluate a novel non-ECG triggered 2D magnetic resonance fingerprinting (MRF) sequence allowing for simultaneous myocardial T₁ and T₂ mapping and cardiac Cine imaging.

METHODS

Cardiac MRF (cMRF) has been recently proposed to provide joint T₁/T₂ myocardial mapping by triggering the acquisition to mid-diastole and relying on a subject-dependent dictionary of MR signal evolutions to generate the maps. In this work, we propose a novel "free-running" (non-ECG triggered) cMRF framework for simultaneous myocardial T₁ and T₂ mapping and cardiac Cine imaging in a single scan. Free-running cMRF is based on a transient state bSSFP acquisition with tiny golden angle radial readouts, varying flip angle and multiple adiabatic inversion pulses. The acquired data is retrospectively gated into several cardiac phases, which are reconstructed with an approach that combines parallel imaging, low rank modelling and patch-based high-order tensor regularization. Free-running cMRF was evaluated in a standardized phantom and ten healthy subjects. Comparison with reference spin-echo, MOLLI, SASHA, T₂-GRASE and Cine was performed.

RESULTS

T₁ and T₂ values obtained with the proposed approach were in good agreement with reference phantom values (ICC(A,1) > 0.99). Reported values for myocardium septum T₁ were 1043 ± 48 ms, 1150 ± 100 ms and 1160 ± 79 ms for MOLLI, SASHA and free-running cMRF respectively and for T₂ of 51.7 ± 4.1 ms and 44.6 ± 4.1 ms for T₂-GRASE and free-running cMRF respectively. Good agreement was observed between free-running cMRF and conventional Cine 2D ejection fraction (bias = -0.83%).

CONCLUSION

The proposed free-running cardiac MRF approach allows for simultaneous assessment of myocardial T₁ and T₂ and Cine imaging in a single scan.

Machine Learning for Rapid Magnetic Resonance Fingerprinting Tissue Property Quantification

Magnetic Resonance Fingerprinting (MRF) is an MRI-based method that can provide quantitative maps of multiple tissue properties simultaneously from a single rapid acquisition. Tissue property maps are generated by matching the complex signal evolutions collected at the scanner to a dictionary of signals derived using Bloch equation simulations. However, in some circumstances, the process of dictionary generation and signal matching can be time-consuming, reducing the utility of this technique. Recently, several groups have proposed using machine learning to accelerate the extraction of quantitative maps from MRF data. This article will provide an overview of current research that combines MRF and machine learning, as well as present original research demonstrating how machine learning can speed up dictionary generation for cardiac MRF.

Water-fat Dixon cardiac magnetic resonance fingerprinting

Purpose

Cardiac magnetic resonance fingerprinting (cMRF) has been recently introduced to simultaneously provide T₁, T₂, and M₀ maps. Here, we develop a 3‐point Dixon‐cMRF approach to enable simultaneous water specific T₁, T₂, and M₀ mapping of the heart and fat fraction (FF) estimation in a single breath‐hold scan.

Methods

Dixon‐cMRF is achieved by combining cMRF with several innovations that were previously introduced for other applications, including a 3‐echo GRE acquisition with golden angle radial readout and a high‐dimensional low‐rank tensor constrained reconstruction to recover the highly undersampled time series images for each echo. Water–fat separation of the Dixon‐cMRF time series is performed to allow for water‐ and fat‐specific T₁, T₂, and M₀ estimation, whereas FF estimation is extracted from the M₀ maps. Dixon‐cMRF was evaluated in a standardized T₁–T₂ phantom, in a water–fat phantom, and in healthy subjects in comparison to current clinical standards: MOLLI, SASHA, T₂‐GRASE, and 6‐point Dixon proton density FF (PDFF) mapping.

Results

Dixon‐cMRF water T₁ and T₂ maps showed good agreement with reference T₁ and T₂ mapping techniques (R² > 0.99 and maximum normalized RMSE ~5%) in a standardized phantom. Good agreement was also observed between Dixon‐cMRF FF and reference PDFF (R² > 0.99) and between Dixon‐cMRF water T₁ and T₂ and water selective T₁ and T₂ maps (R² > 0.99) in a water–fat phantom. In vivo Dixon‐cMRF water T₁ values were in good agreement with MOLLI and water T₂ values were slightly underestimated when compared to T₂‐GRASE. Average myocardium septal T₁ values were 1129 ± 38 ms, 1026 ± 28 ms, and 1045 ± 32 ms for SASHA, MOLLI, and the proposed water Dixon‐cMRF. Average T₂ values were 51.7 ± 2.2 ms and 42.8 ± 2.6 ms for T₂‐GRASE and water Dixon‐cMRF, respectively. Dixon‐cMRF FF maps showed good agreement with in vivo PDFF measurements (R² > 0.98) and average FF in the septum was measured at 1.3%.

Conclusion

The proposed Dixon‐cMRF allows to simultaneously quantify myocardial water T₁, water T₂, and FF in a single breath‐hold scan, enabling multi‐parametric T₁, T₂, and fat characterization. Moreover, reduced T₁ and T₂ quantification bias caused by water–fat partial volume was demonstrated in phantom experiments.

Cardiac Magnetic Resonance Fingerprinting: Technical Developments and Initial Clinical Validation

PURPOSE OF REVIEW

Magnetic resonance imaging (MRI) has enabled non-invasive myocardial tissue characterization in a wide range of cardiovascular diseases by quantifying several tissue specific parameters such as T1, T2, and T2* relaxation times. Simultaneous assessment of these parameters has recently gained interest to potentially improve diagnostic accuracy and enable further understanding of the underlying disease. However, these quantitative maps are usually acquired sequentially and are not necessarily co-registered, making multi-parametric analysis challenging. Magnetic resonance fingerprinting (MRF) has been recently introduced to unify and streamline parametric mapping into a single simultaneous, multi-parametric, fully co-registered, and efficient scan. Feasibility of cardiac MRF has been demonstrated and initial clinical validation studies are ongoing. Provide an overview of the cardiac MRF framework, recent technical developments and initial undergoing clinical validation.

RECENT FINDINGS

Cardiac MRF has enabled the acquisition of co-registered T1 and T2 maps in a single, efficient scan. Initial results demonstrate feasibility of cardiac MRF in healthy subjects and small patient cohorts. Current in vivo results show a small bias and comparable precision in T1 and T2 with respect to conventional clinical parametric mapping approaches. This bias may be explained by several confounding factors such as magnetization transfer and field inhomogeneities, which are currently not included in the cardiac MRF model. Initial clinical validation for cardiac MRF has demonstrated good reproducibility in healthy subjects and heart transplant patients, reduced artifacts in inflammatory cardiomyopathy patients and good differentiation between hypertrophic cardiomyopathy and healthy controls. Cardiac MRF has emerged as a novel technique for simultaneous, multi-parametric, and co-registered mapping of different tissue parameters. Initial efforts have focused on enabling T1, T2, and fat quantification; however this approach has the potential of enabling quantification of several other parameters (such as T2*, diffusion, perfusion, and flow) from a single scan. Initial results in healthy subjects and patients are promising, thus further clinical validation is now warranted.

Magnetic resonance fingerprinting Part 1: Potential uses, current challenges, and recommendations

Magnetic resonance fingerprinting (MRF) is a powerful quantitative MRI technique capable of acquiring multiple property maps simultaneously in a short timeframe. The MRF framework has been adapted to a wide variety of clinical applications, but faces challenges in technical development, and to date has only demonstrated repeatability and reproducibility in small studies. In this review, we discuss the current implementations of MRF and their use in a clinical setting. Based on this analysis, we highlight areas of need that must be addressed before MRF can be fully adopted into the clinic and make recommendations to the MRF community on standardization and validation strategies of MRF techniques. Level of Evidence: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2020;51:675-692.

Comprehensive Evaluation of B1+-corrected FISP-based Magnetic Resonance Fingerprinting: Accuracy, Repeatability and Reproducibility of T1 and T2 Relaxation Times for ISMRM/NIST System Phantom and Volunteers

Purpose:

This study aimed to evaluate comprehensively; accuracy, repeatability and reproducibility of T₁ and T₂ relaxation times measured by magnetic resonance fingerprinting using B1+-corrected fast imaging with steady-state precession (FISP–MRF).

Methods:

The International Society of Magnetic Resonance in Medicine/National Institute of Standards and Technology (ISMRM/NIST) phantom was scanned for 100 days, and six healthy volunteers for 5 days using a FISP–MRF prototype sequence. Accuracy was evaluated on the phantom by comparing relaxation times measured by FISP–MRF with the reference values provided by the phantom manufacturer. Daily repeatability was characterized as the coefficient of variation (CV) of the measurements over 100 days for the phantom and over 5 days for volunteers. In addition, the cross-scanner reproducibility was evaluated in volunteers.

Results:

In the phantom study, T₁ and T₂ values from FISP–MRF showed a strong linear correlation with the reference values of the phantom (R² = 0.9963 for T₁; R² = 0.9966 for T₂). CVs were <1.0% for T₁ values larger than 300 ms, and <3.0% for T₂ values across a wide range. In the volunteer study, CVs for both T₁ and T₂ values were <5.0%, except for one subject. In addition, all T₂ values estimated by FISP–MRF in vivo were lower than those measured with conventional mapping sequences reported in previous studies. The cross-scanner variation of T₁ and T₂ showed good agreement between two different scanners in the volunteers.

Conclusion:

B1+-corrected FISP-MRF showed an acceptable accuracy, repeatability and reproducibility in the phantom and volunteer studies.

High-dimensionality undersampled patch-based reconstruction (HD-PROST) for accelerated multi-contrast MRI

PURPOSE

To develop a new high-dimensionality undersampled patch-based reconstruction (HD-PROST) for highly accelerated 2D and 3D multi-contrast MRI.

METHODS

HD-PROST jointly reconstructs multi-contrast MR images by exploiting the highly redundant information, on a local and non-local scale, and the strong correlation shared between the multiple contrast images. This is achieved by enforcing multi-dimensional low-rank in the undersampled images. 2D magnetic resonance fingerprinting (MRF) phantom and in vivo brain acquisitions were performed to evaluate the performance of HD-PROST for highly accelerated simultaneous T1 and T2 mapping. Additional in vivo experiments for reconstructing multiple undersampled 3D magnetization transfer (MT)-weighted images were conducted to illustrate the impact of HD-PROST for high-resolution multi-contrast 3D imaging.

RESULTS

In the 2D MRF phantom study, HD-PROST provided accurate and precise estimation of the T1 and T2 values in comparison to gold standard spin echo acquisitions. HD-PROST achieved good quality maps for the in vivo 2D MRF experiments in comparison to conventional low-rank inversion reconstruction. T1 and T2 values of white matter and gray matter were in good agreement with those reported in the literature for MRF acquisitions with reduced number of time point images (500 time point images, ~2.5 s scan time). For in vivo MT-weighted 3D acquisitions (6 different contrasts), HD-PROST achieved similar image quality than the fully sampled reference image for an undersampling factor of 6.5-fold.

CONCLUSION

HD-PROST enables multi-contrast 2D and 3D MR images in a short acquisition time without compromising image quality. Ultimately, this technique may increase the potential of conventional parameter mapping.

Simultaneous multislice cardiac magnetic resonance fingerprinting using low rank reconstruction

This study introduces a technique for simultaneous multislice (SMS) cardiac magnetic resonance fingerprinting (cMRF), which improves the slice coverage when quantifying myocardial T_1, T₂ , and M₀ . The single-slice cMRF pulse sequence was modified to use multiband (MB) RF pulses for SMS imaging. Different RF phase schedules were used to excite each slice, similar to POMP or CAIPIRINHA, which imparts tissues with a distinguishable and slice-specific magnetization evolution over time. Because of the high net acceleration factor (R = 48 in plane combined with the slice acceleration), images were first reconstructed with a low rank technique before matching data to a dictionary of signal timecourses generated by a Bloch equation simulation. The proposed method was tested in simulations with a numerical relaxation phantom. Phantom and in vivo cardiac scans of 10 healthy volunteers were also performed at 3 T. With single-slice acquisitions, the mean relaxation times obtained using the low rank cMRF reconstruction agree with reference values. The low rank method improves the precision in T₁ and T₂ for both single-slice and SMS cMRF, and it enables the acquisition of maps with fewer artifacts when using SMS cMRF at higher MB factors. With this technique, in vivo cardiac maps were acquired from three slices simultaneously during a breathhold lasting 16 heartbeats. SMS cMRF improves the efficiency and slice coverage of myocardial T₁ and T₂ mapping compared with both single-slice cMRF and conventional cardiac mapping sequences. Thus, this technique is a first step toward whole-heart simultaneous T₁ and T₂ quantification with cMRF.